Mitogenomic evolutionary rates in bilateria are influenced by parasitic lifestyle and locomotory capacity

The evidence that parasitic animals exhibit elevated mitogenomic evolutionary rates is inconsistent and limited to Arthropoda. Similarly, the evidence that mitogenomic evolution is faster in species with low locomotory capacity is limited to a handful of animal lineages. We hypothesised that these two variables are associated and that locomotory capacity is a major underlying factor driving the elevated rates in parasites. Here, we study the evolutionary rates of mitogenomes of 10,906 bilaterian species classified according to their locomotory capacity and parasitic/free-living life history. In Bilateria, evolutionary rates were by far the highest in endoparasites, much lower in ectoparasites with reduced locomotory capacity and free-living lineages with low locomotory capacity, followed by parasitoids, ectoparasites with high locomotory capacity, and finally micropredatory and free-living lineages. The life history categorisation (parasitism) explained ≈45%, locomotory capacity categorisation explained ≈39%, and together they explained ≈56% of the total variability in evolutionary rates of mitochondrial protein-coding genes in Bilateria. Our findings suggest that these two variables play major roles in calibrating the mitogenomic molecular clock in bilaterian animals.


Field-specific reporting
Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

Life sciences
Behavioural & social sciences Ecological, evolutionary & environmental sciences For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf

Ecological, evolutionary & environmental sciences study design
All studies must disclose on these points even when the disclosure is negative.

Study description
Research sample All data used in this study were retrieved from the NCBI's GenBank RefSeq database (https://www.ncbi.nlm.nih.gov/refseq/). Source data are provided with this paper.
We extracted 12 protein-coding genes from 10,914 mitogenomes of bilaterian animals, built a phylum-level topology-constrained phylogenetic tree using this dataset, and extracted branch lengths. The dataset was classified according to the life history into five categories: endoparasites (EndoP), ectoparasites (EctoP), parasitoids, micropredators (MP), and free-living (F). We further divided the dataset into three locomotory capacity categories. 1. High (H), comprising all species expected to rely on locomotion for pursuit and evasion of prey/predators. 2. Low (L), comprising all species that have merely a rudimentary locomotory capacity (i.e. not expected to rely on locomotion for pursuit and evasion of prey/predators). 3. Because the distinction between the high and low locomotory capacity species is blurry in many cases, we designed a third category, Intermediate LC (I), with the aim to mop up the noise produced by these difficult-to-classify taxa, and make sure that the High and Low categories do not overlap. This category comprises species that would be expected to possess more than a rudimentary locomotory capacity, but also rely on strategies other than locomotion to evade/pursue predators/prey. We organised the dataset in a hierarchical manner, by further subdividing it according to major taxonomic categories: phylum, class and order. First we conducted pairwise comparisons of branch lengths between different groups using Tukey HSD tests and PGLS ANOVA. To assess the relative impacts of different variables on branch length, we used two multilevel regression algorithms designed to account for the phylogenetic relatedness of data: linear fixed-effect models accounting for kinship implemented in the lmekin function in coxme, and phylogenetic multilevel Bayesian models implemented in brms. For both analyses, we used a matrix of phylogenetic distances extracted from the phylogenetic tree. We log-transformed the branch length data to reduce the nonnormality of distribution. For these analyses, branch length was the dependent variable, and life history and locomotory capacity categorisations were independent variable. We also conducted analyses after removing the outliers from the dataset. Finally, we conducted selection pressure analyses. As parasitism and locomotory capacity are partially overlapping variables, we attempted to discern their impacts using further subsets of data. To reduce the effect of locomotory capacity variability, we focused only on the Low locomotory capacity category and divided it along the life history lines. To remove the effect of parasitism on the locomotory capacity classification, we conducted analyses using only the free-living species.
The objective of the study was to research the evolution of mitochondrial genome in bilaterian animals. Nonbilaterians possess highly divergent mitogneomes, which would have made comparative analyses difficult to conduct, and comprise only about 2% of all available animal mitogenomes, so we opted to study only bilaterian animals. The dataset was retrieved from NCBI's GenBank. The dataset for phylogenetic analysis comprised 10,914 bilaterian mitogenomes (+ 8 nonbilaterian species as outgroups), or about 2% of all recognised bilaterian species according to ITIS (521,682). The dataset for statistical analyses comprised 11,906 mitogenomes,